电离层TEC预报模型的卡尔曼滤波改进方法

Improvement of forecasting models of ionospheric TEC by Kalman filter

针对直接使用IGS公布的原始数据对电离层TEC进行预报时存在原始数据含有随机噪声等问题,提出将卡尔曼滤波作为预处理方式引入电离层TEC预报,用以减小噪声对于预报模型的影响。实验结果表明,卡尔曼滤波对电离层TEC数据具有很好的降低噪声的作用,使用滤波后的数据建立组合模型能够提高模型的预测精度。

Aiming at the problem that the original data published by IGS contain random noise in forecasting the ionospheric TEC,the paper proposed to use Kalman filter in the forecasting as a pre-processing method,in order to eliminate the impact of noise on forecasting models.Experimental result showed that the noise could be efficiently reduced by Kalman filter for ionospheric TEC data,and the forecasting accuracy of the models established by the data after filtering could be improved.